class_docstr: Hessian update strategy with full dimensional internal representation.
      
docstr: Initialize internal matrix.
  
  Allocate internal memory for storing and updating
  the Hessian or its inverse.
  
  Parameters
  ----------
  n : int
      Problem dimension.
  approx_type : {'hess', 'inv_hess'}
      Selects either the Hessian or the inverse Hessian.
      When set to 'hess' the Hessian will be stored and updated.
      When set to 'inv_hess' its inverse will be used instead.
docstr_tok: ["Initialize","internal","matrix",".","Allocate","internal","memory","for","storing","and","updating","the","Hessian","or","its","inverse",".","Parameters","--","--","--","--","--","n",":","int","Problem","dimension",".","approx_type",":","{","'hess","'",",","'inv_hess","'","}","Selects","either","the","Hessian","or","the","inverse","Hessian",".","When","set","to","'hess","'","the","Hessian","will","be","stored","and","updated",".","When","set","to","'inv_hess","'","its","inverse","will","be","used","instead","."]
code: def initialize(self, n, approx_type):
      """Initialize internal matrix.
  
      Allocate internal memory for storing and updating
      the Hessian or its inverse.
  
      Parameters
      ----------
      n : int
          Problem dimension.
      approx_type : {'hess', 'inv_hess'}
          Selects either the Hessian or the inverse Hessian.
          When set to 'hess' the Hessian will be stored and updated.
          When set to 'inv_hess' its inverse will be used instead.
      """
      self.first_iteration = True
      self.n = n
      self.approx_type = approx_type
      if approx_type not in ("hess", "inv_hess"):
          raise ValueError(
              "`approx_type` must be 'hess' or 'inv_hess'."
          )
      # Create matrix
      if self.approx_type == "hess":
          self.B = np.eye(n, dtype=float)
      else:
          self.H = np.eye(n, dtype=float)
  
imports: from __future__ import division, print_function, absolute_import
  import numpy
  from numpy.linalg import norm
  from scipy.linalg import get_blas_funcs
  from warnings import warn
label_desc: Use image node_id 2 for calling the FullHessianUpdateStrategy obj's underlying member method code with example usage: obj.initialize(n, approx_type) without return types